title: On numerical simulations of integrate-and-fire neural networks.
abstract: It is shown that very small time steps are required to reproduce correctly the synchronization properties of large networks of integrate-and-fire neurons when the differential system describing their dynamics is integrated with the standard Euler or second-order Runge-Kutta algorithms. The reason for that behavior is analyzed, and a simple improvement of these algorithms is proposed.
authors.affiliation: Centre de Physique Théorique UPR014 CNRS, Ecole Polytechnique, Palaiseau, France.
authors.forename: D
authors.initials: D
authors.lastname: Hansel
authors.forename: G
authors.initials: G
authors.lastname: Mato
authors.forename: C
authors.initials: C
authors.lastname: Meunier
authors.forename: L
authors.initials: L
authors.lastname: Neltner
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000465:Algorithms; D003198:Computer Simulation; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D015203:Reproducibility of Results